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Salesforce-AI-Specialist Latest Test Materials | Salesforce-AI-Specialist Latest Braindumps Ebook

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Salesforce Salesforce-AI-Specialist Exam Syllabus Topics:

Topic
Details

Topic 1

Agentforce Tools: In this topic, AI specialists get knowledge using agents when it is appropriate. Moreover, the topic explains the working of agents and reasoning engine powers Agentforce. Lastly, the topic focuses on managing and monitoring agent adoption.

Topic 2

Einstein Trust Layer: This section evaluates the skills of Salesforce AI specialists responsible for implementing security protocols and safeguarding data privacy. It emphasizes the security, privacy, and foundational features of the Einstein Trust Layer.

Topic 3

Model Builder: This portion of the exam focuses on Salesforce AI specialists' expertise in working with AI models within Salesforce environments. Candidates will need to demonstrate knowledge of when to use the Model Builder and how to configure standard, custom, or Bring Your Own Large Language Model (BYOLLM) generative models to meet business needs.

Topic 4

Generative AI in CRM Applications: This part of the exam assesses AI specialists’ knowledge of generative AI within CRM systems. It covers the use of generative AI features in Einstein for Sales and Einstein for Service.

Topic 5

Prompt Builder: This section evaluates the expertise of AI specialists working with Salesforce's AI tools. It focuses on the Prompt Builder feature, requiring candidates to understand its usage based on business needs.

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Salesforce Certified AI Specialist Exam Sample Questions (Q42-Q47):

NEW QUESTION # 42
Universal Containers wants to make a sales proposal and directly use data from multiple unrelated objects (standard and custom) in a prompt template.
What should the AI Specialist recommend?

A. Create a Flex template to add resources with standard and custom objects as inputs.
B. Create a prompt template passing in a special custom object that connects the records temporarily,
C. Create a prompt template-triggered flow to access the data from standard and custom objects.

Answer: A

Explanation:
Universal Containers needs to generate a sales proposal using data from multiple unrelated standard and custom objects within a prompt template. The most effective way to achieve this is by using a Flex template.
Flex templates in Salesforce allow AI specialists to create prompt templates that can accept inputs from multiple sources, including various standard and custom objects. This flexibility enables the direct use of data from unrelated objects without the need to create intermediary custom objects or complex flows.
Reference:
Salesforce AI Specialist Documentation - Flex Templates: Explains how Flex templates can be utilized to incorporate data from multiple sources, providing a flexible solution for complex data requirements in prompt templates.

NEW QUESTION # 43
Universal Containers (UC) wants to assess Salesforce's generative features but has concerns over its company data being exposed to third- party large language models (LLMs). Specifically, UC wants the following capabilities to be part of Einstein's generative AI service.
No data is used for LLM training or product improvements by third- party LLMs.
No data is retained outside of UC's Salesforce org.
The data sent cannot be accessed by the LLM provider.
Which property of the Einstein Trust Layer should the AI Specialist highlight to UC that addresses these requirements?

A. Zero-Data Retention Policy
B. Data Masking
C. Prompt Defense

Answer: A

Explanation:
Universal Containers (UC) has concerns about data privacy when using Salesforce's generative AI features, particularly around preventing third-party LLMs from accessing or retaining their data. The Zero-Data Retention Policy in the Einstein Trust Layer is designed to address these concerns by ensuring that:
No data is used for training or product improvements by third-party LLMs.
No data is retained outside of the customer's Salesforce organization.
The LLM provider cannot access any customer data.
This policy aligns perfectly with UC's requirements for keeping their data safe while leveraging generative AI capabilities.
Prompt Defense and Data Masking are also security features, but they do not directly address the concerns related to third-party data access and retention.
Reference:
Salesforce Einstein Trust Layer Documentation: https://help.salesforce.com/s/articleView?id=sf.einstein_trust_layer.htm

NEW QUESTION # 44
A service agent is looking at a custom object that stores travel information. They recently received a weather alert and now need to cancel flights for the customers that are related with this itinerary. The service agent needs to review the Knowledge articles about canceling and rebooking the customer flights.
Which Einstein Copilot capability helps the agent accomplish this?

A. Invoke a flow which makes a call to external data to create a Knowledge article.
B. Generate a Knowledge article based off the prompts that the agent enters to create steps to cancel flights.
C. Execute tasks based on available actions, answering questions using information from accessible Knowledge articles.

Answer: B

Explanation:
In this scenario, theEinstein Copilotcapability that best helps the agent is its ability toexecute tasks based on available actionsandanswer questionsusing data from Knowledge articles. Einstein Copilot can assist the service agent by providing relevant Knowledge articles on canceling and rebooking flights, ensuring that the agent has access to the correct steps and procedures directly within the workflow.
This feature leverages the agent's existing context (the travel itinerary) and provides actionable insights or next steps from the relevant Knowledge articles to help the agent quickly resolve the customer's needs.
The other options are incorrect:
* Brefers to invoking a flow to create a Knowledge article, which is unrelated to the task of retrieving existing Knowledge articles.
* Cfocuses on generating Knowledge articles, which is not the immediate need for this situation where the agent requires guidance on existing procedures.
References:
* Salesforce Documentation onEinstein Copilot
* Trailhead Module onEinstein for Service

NEW QUESTION # 45
An AI Specialist is setting up a new org and needs to ensure that users can create and execute prompt templates. The AI Specialist is unsure which roles are necessary for these tasks.
Which permission sets should the AI Specialist assign to users who need to create and execute prompt templates?

A. Prompt Template Manager for creating templates and Data Cloud Admin for executing templates
B. Data Cloud Admin for creating templates and Prompt Template User for executing templates
C. Prompt Template Manager for creating templates and Prompt Template User for executing templates

Answer: C

Explanation:
To effectively manage and use prompt templates, two distinct permission sets are required:
* Prompt Template Manager: This permission set allows users to create prompt templates. It provides the necessary access to define templates, which can be shared and utilized across the organization.
* Prompt Template User: This permission set is designed for users who need to execute the templates. It provides the ability to interact with pre-designed prompts and generate outcomes based on these templates.
TheData Cloud Adminpermission set is not directly relevant to creating or executing prompt templates but is more focused on managing the Data Cloud.

NEW QUESTION # 46
A sales manager is using Agent Assistant to streamline their daily tasks. They ask the agent to Show me a list of my open opportunities.
How does the large language model (LLM) in Agentforce identify and execute the action to show the sales manager a list of open opportunities?

A. The LLM uses a static set of rules to match the user's request with predefined topics and actions, bypassing the need for dynamic interpretation and planning.
B. Using a dialog pattern. the LLM matches the user query to the available topic, action and steps then performs the steps for each action, such as retrieving a fast of open opportunities.
C. The LLM interprets the user's request, generates a plan by identifying the apcMopnete topics and actions, and executes the actions to retrieve and display the open opportunities

Answer: C

Explanation:
Agentforce's LLM dynamically interprets natural language requests (e.g., "Show me open opportunities"), generates an execution plan using the planner service, and retrieves data via actions (e.g., querying Salesforce records). This contrasts with static rules (B) or rigid dialog patterns (C), which lack contextual adaptability. Salesforce documentation highlights the planner's role in converting intents into actionable steps while adhering to security and business logic.

NEW QUESTION # 47
......

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